Microalgae are exceptional organisms from a nutritional perspective, boasting an array of bioactive compounds that have long justified their incorporation into human diets. In this study, we explored the potential of five microalgae species: Nannochloropsis sp., Tetraselmis chuii, Chaetoceros muelleri, Thalassiosira weissflogii, and Tisochrysis lutea. We conducted comprehensive analyses of their nutritional profiles, encompassing protein content, individual amino acid composition, mineral and trace element levels, fatty acid profiles (including saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and polyunsaturated fatty acids (PUFAs)), polyphenol compositions, and vitamin B content. The antioxidant activity of the ethanolic extracts was evaluated using two methods: ABTS and DPPH radical scavenging assay. The total protein content of the microalgae ranged from 34.09 ± 0.39% to 42.45 ± 0.18%, with the highest concentration observed in T. weissflogii. Essential amino acids such as histidine, threonine, lysine, valine, isoleucine, leucine, phenylalanine, and methionine were present in concentrations ranging from 0.53 ± 0.02 to 12.55 ± 2.21 g/16 g N. Glutamic acid emerged as the most abundant amino acid, with concentrations ranging from 6.73 ± 0.82 to 12.55 ± 2.21 g/16 g N. Among the microalgae species, T. chuii exhibited the highest concentrations of calcium (Ca) and manganese (Mn), while C. muelleri showed prominence in magnesium (Mg), sodium (Na), and iron (Fe). T. weissflogii stood out for its potassium (K) content, and T. lutea contained notable amounts of copper (Cu), zinc (Zn), and lead (Pb). Regarding fatty acid profiles, Nannochloropsis sp. and T. chuii were predominantly composed of SFA, while C. muelleri and T. weissflogii were rich in MUFA. PUFAs dominated the fatty acid profile of T. lutea, which also exhibited the most diverse range of polyphenolic substances. We also analyzed the B vitamin content, with T. lutea displaying the highest concentrations of niacin (B3) and riboflavin (B2). Antioxidant activity was confirmed for all microalgae tested using DPPH and ABTS radical IC50 (mg/mL) converted to Trolox equivalent (TEAC). These findings underscore the substantial potential of the examined microalgae species as sources of biologically valuable substances characterized by rapid growth and relatively undemanding cultivation conditions.

Nutrient requirement for crop growth, defined as the amount of nutrient that crops take up from soil to produce a specific grain yield, is a key parameter in determining fertilizer application rate. However, existing studies primarily focus on identifying nitrogen (N), phosphorus (P), and potassium (K) requirements solely in relation to grain yield, neglecting grain protein content, a crucial index for wheat grain quality. Addressing this gap, we conducted multi-site, multi-cultivar, and multi-year field trials across three ecological regions of China from 2016 to 2020 to elucidate variations in nutrient requirements for grain yield and grain protein. The research findings revealed that wheat grain yield ranged from 4.1 to 9.3 Mg ha-1 (average 6.9 Mg ha-1) and grain protein content ranged from 98 to 157 g kg-1 (average 127 g kg-1) across the three regions. Notably, the N requirement exhibited a nonlinear correlation with the wheat grain yield but a linear increase with increasing grain protein, while the P and K requirements positively correlated with grain yield and protein content. Regression models were formulated to determine the nutrient requirements (MENR), enabling the prediction of N, P, and K requirements for leading cultivars with varying grain yields and protein contents. Implementing nutrient requirements based on MENR projections resulted in substantial reductions in fertilizer rates: 22.0 kg ha-1 N (10.7 %), 9.9 kg ha-1 P (20.2 %), and 8.1 kg ha-1 K (16.3 %). This translated to potential savings of 0.4 Mt. N, 0.23 Mt. P, and 0.17 Mt. K, consequently mitigating 5.5 Mt. CO2 greenhouse-gas emission and yielding an economic benefit of 0.8 billion US$ annually in China. These findings underscore the significance of considering grain yield and protein content in estimating nutrient requirements for fertilizer recommendations to realize high-yielding, high-protein wheat production, and minimize overfertilization and associated environmental risks.

The increasing use of photoselective nets (PNs) raises the question of their influence on pollen traits. We aimed to evaluate the effect of PNs (yellow, pearl, and grey) on the pollen of \'Matua\' and \'Tomuri\' Actinidia deliciosa cultivars. The pollen size and the exine were studied with a light microscopy and a scanning electron microscopy, and the fertility was analysed by a viability assay and in vitro germination. The total soluble proteins (TSPs) and sugars (TSSs) were quantified by colorimetric assays. The molecular structure of the pollen grain\'s wall was analysed by a Raman spectroscopy. The pollen from the plants under the PNs had a larger width and area and a lower germination rate. No significant changes were observed in the exine\'s microperforations. The TSP and TSS contents were influenced by the cultivar and PNs (particularly the pearl PN). The Raman spectra of the pollen from the plants grown under the nets presented some bands that significantly shifted from their original position, indicating differences in the vibration modes of the molecules, but no overall changes at their structural or organisation level were found. Our study showed that the PNs could influence several pollen traits, with the pearl PN inducing greater modifications. Our results also support the idea that cultivars affect the outcome of some characteristics.

Microbial proteins represent a promising solution to address the escalating global demand for protein, particularly in regions with limited arable land. Yeasts, such as Saccharomyces cerevisiae, are robust and safe protein-producing strains. However, the utilization of non-conventional yeast strains for microbial protein production has been hindered, partly due to a lack of comprehensive understanding of protein production traits. In this study, we conducted experimental analyses focusing on the growth, protein content, and amino acid composition of nine yeast strains, including one S. cerevisiae strain, three Yarrowia lipolytica strains, and five Pichia spp. strains. We identified that, though Y. lipolytica and Pichia spp. strains consumed glucose at a slower rate compared to S. cerevisiae, Pichia spp. strains showed a higher cellular protein content, and Y. lipolytica strains showed a higher glucose-to-biomass/protein yield and methionine content. We further applied computational approaches to explain that metabolism economy was the main underlying factor for the limited amount of scarce/carbon-inefficient amino acids (such as methionine) within yeast cell proteins. We additionally verified that the specialized metabolism was a key reason for the high methionine content in Y. lipolytica strains, and proposed Y. lipolytica strain as a potential producer of high-quality single-cell protein rich in scarce amino acids. Through experimental evaluation, we identified Pichia jadinii CICC 1258 as a potential strain for high-quality protein production under unfavorable pH/temperature conditions. Our work suggests a promising avenue for optimizing microbial protein production, identifying the factors influencing amino acid composition, and paving the way for the use of unconventional yeast strains to meet the growing protein demands.

This study explores the interplay between nitrogen doses and seeding rates on wheat yield, biomass, and protein content. Utilizing tools such as the Normalized Difference Vegetation Index (NDVI), Soil Plant Analysis Development (SPAD) measurements, and canopy temperature (CT), we conducted experiments over five growing seasons. The treatments included three nitrogen levels (0, 60, 120 kg/ha) and three seeding rates (300, 400, 500 seeds/m2) in a split-plot design with 90 plots and two replications. Our results show that an intermediate nitrogen dose (60 kg/ha) combined with a moderate seed rate (400 seeds/m2) enhances wheat yield by 22.95%. Reduced nitrogen levels increased protein content, demonstrating wheat\'s adaptive mechanisms under nitrogen constraints. NDVI analysis highlighted significant growth during the tillering phase with high nitrogen, emphasizing early-stage nutrient management. SPAD measurements showed that early nitrogen applications boost chlorophyll content, essential for vigorous early growth, while CT data indicate that optimal nitrogen and seed rates can effectively modulate plant stress responses. As crops mature, the predictive capacity of NDVI declines, indicating the need for adjusted nitrogen strategies. Collectively, these findings advocate for refined management of nitrogen and seeding rates, integrating NDVI, SPAD, and CT assessments to enhance yields and promote sustainable agricultural practices while minimizing environmental impacts.

The escalating global population is anticipated to intensify the demand for high-quality proteins, necessitating the exploration of alternative protein sources. Edible insects are a promising solution, owing to their nutritional richness and sustainability. However, their digestibility and protein quality, particularly after culinary treatment, remains underexplored. In the present study, we investigated the effects of various culinary treatments on the protein digestibility of two insect species, Tenebrio molitor and Gryllus assimilis. Our findings revealed that culinary treatments such as boiling, roasting, drying, and microwave heating significantly influenced the digestibility of both insect species. Notably, drying emerged as the most effective method, leading to a substantial increase in digestibility. Furthermore, we assessed protein quality using the digestible indispensable amino acid score (DIAAS) and found that the choice of the calculation method significantly influenced the evaluation of protein quality. By including the sum of the anhydrous amino acids, we eliminated the potential overestimation of protein content and obtained a more reliable assessment of protein quality. Our results underscore the importance of culinary treatments and calculation methods in determining the suitability of insects as protein sources for human nutrition.

The coordinated interspecific variation in leaf traits and leaf lifespan is known as the leaf economic spectrum (LES). The limitation of CO2 diffusion to chloroplasts within the lamina is significant in C3 photosynthesis, resulting in a shortage of CO2 for Rubisco. Although Rubisco CO2/O2 specificity (SC/O) should be adaptively adjusted in response to the interspecific variation in CO2 concentrations [CO2] associated with Rubisco, SC/O variations across species along the LES remain unknown. We investigated the coordination among leaf traits, including SC/O, CO2 conductance, leaf protein content, and leaf mass area, across 23 woody C3 species coexisting on an oceanic island through phylogenetic correlation analyses. A high SC/O indicates a high CO2 specificity of Rubisco. SC/O was negatively correlated with [CO2] at Rubisco and total CO2 conductance within lamina, while it was positively correlated with leaf protein across species, regardless of phylogenetic constraint. A simulation analysis shows that the optimal SC/O for maximizing photosynthesis depends on both [CO2] at Rubisco sites and leaf protein per unit leaf area. SC/O is a key parameter along the LES axis and is crucial for maximizing photosynthesis across species and the adaptation of woody plants.

Genomic selection (GS) is a marker-based selection method used to improve the genetic gain of quantitative traits in plant breeding. A large number of breeding datasets are available in the soybean database, and the application of these public datasets in GS will improve breeding efficiency and reduce time and cost. However, the most important problem to be solved is how to improve the ability of across-population prediction. The objectives of this study were to perform genomic prediction (GP) and estimate the prediction ability (PA) for seed oil and protein contents in soybean using available public datasets to predict breeding populations in current, ongoing breeding programs. In this study, six public datasets of USDA GRIN soybean germplasm accessions with available phenotypic data of seed oil and protein contents from different experimental populations and their genotypic data of single-nucleotide polymorphisms (SNPs) were used to perform GP and to predict a bi-parent-derived breeding population in our experiment. The average PA was 0.55 and 0.50 for seed oil and protein contents within the bi-parents population according to the within-population prediction; and 0.45 for oil and 0.39 for protein content when the six USDA populations were combined and employed as training sets to predict the bi-parent-derived population. The results showed that four USDA-cultivated populations can be used as a training set individually or combined to predict oil and protein contents in GS when using 800 or more USDA germplasm accessions as a training set. The smaller the genetic distance between training population and testing population, the higher the PA. The PA increased as the population size increased. In across-population prediction, no significant difference was observed in PA for oil and protein content among different models. The PA increased as the SNP number increased until a marker set consisted of 10,000 SNPs. This study provides reasonable suggestions and methods for breeders to utilize public datasets for GS. It will aid breeders in developing GS-assisted breeding strategies to develop elite soybean cultivars with high oil and protein contents.

Protein content (PC) is crucial to the nutritional quality of soybean [Glycine max (L.) Merrill]. In this study, a total of 266 accessions were used to perform a genome-wide association study (GWAS) in three tested environments. A total of 23,131 high-quality SNP markers (MAF ≥ 0.02, missing data ≤ 10%) were identified. A total of 40 association signals were significantly associated with PC. Among them, five novel quantitative trait nucleotides (QTNs) were discovered, and another 32 QTNs were found to be overlapping with the genomic regions of known quantitative trait loci (QTL) related to soybean PC. Combined with GWAS, metabolome and transcriptome sequencing, 59 differentially expressed genes (DEGs) that might control the change in protein content were identified. Meantime, four commonly upregulated differentially abundant metabolites (DAMs) and 29 commonly downregulated DAMs were found. Remarkably, the soybean gene Glyma.08G136900, which is homologous with Arabidopsis hydroxyproline-rich glycoproteins (HRGPs), may play an important role in improving the PC. Additionally, Glyma.08G136900 was divided into two main haplotype in the tested accessions. The PC of haplotype 1 was significantly lower than that of haplotype 2. The results of this study provided insights into the genetic mechanisms regulating protein content in soybean.

Increasing amounts of amino-functionalized polystyrene nanoplastics (PS-NH2) are entering aquatic ecosystems, raising concerns. Hence, this study investigated 96-h acute toxicity of PS-NH2 and its combination with the pesticide atrazine (ATZ) in the absence/presence of humic acid (HA) on the microalgae Chlorella vulgaris (C. vulgaris). Results showed that both PS-NH2 and PS-NH2+ATZ reduced algal growth, photosynthetic pigments, protein content, and antioxidant capacity, while increasing enzymatic activities. Gene expression related to oxidative stress was altered in C. vulgaris exposed to these treatments. Morphological and intracellular changes were also observed. The combined toxicity of PS-NH2+ATZ demonstrated a synergistic effect, but the addition of environmentally relevant concentration of HA significantly alleviated its toxicity to C. vulgaris, indicating an antagonistic effect due to the emergence of an eco-corona, and entrapment and sedimentation of PS-NH2+ATZ particles by HA. This study firstly highlights the role of HA in mitigating the toxicity of PS-NH2 when combined with other harmful compounds, enhancing our understanding of HA\'s presence in the environment.